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Results published in May

Requirements for a decision support tool – Railway capacity IT support

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Description: This deliverable describes the current Shift2Rail work with demonstrator concept – a simulation module Proton and an intelligent planning module M2 – Timo. The intelligent planning module includes a data handling and visualisation component M2 and a timetable modification component, TIMO. Proton is a powerful macrosimulator for national networks. or the future Rail System Architecture.

Target audience: All rail stakeholders; Final users (travellers and freight transport users); Operators (rail operator companies); Infrastructure management companies

How it brings us closer to achieving better rail for Europe: It brings us closer by helping European railways develop future network management processes and methods for rail operators with decision support and automation. It improves the current capacity processes and solves complex capacity problems with many involved actors. The research also contributes to automation in timetables and operational traffic, as well as interaction between actors.

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  • Proton (formerly called Prism) was developed in Cross-Cutting Activities projects Plasa 1 and Plasa 2
  • M2-Timo and Proton, research is done in FR8Rail II and FR8Rail III projects.

Long Term Evolution (LTE) equipment under challenging wireless scenarios

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Description: This deliverable evaluates the capabilities of the Long Term Evolution (LTE) V2X technology to fulfil the required performance for a Wireless Train Backbone (WLTB) operating in different challenging environments: depots, stations, tracks and tunnels.

Target audience: Operators (rail operator companies); Suppliers (vehicle and part manufacturers)

How it brings us closer to achieving better rail for Europe: It brings us closer by allowing us to identify the gaps between WLTB requirements and a WLTB based on LTE V2X technology and paves the road towards a 5G powered rail for Europe.

More information on this topic: TD 1.2 – Train Control and Monitoring System Demonstrator


Summary of existing relevant projects and state-of-the-art of AI application in railways

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Description: This deliverable provides a comprehensive review of research projects and scientific papers addressing the state-of-the-art of AI in the railway applied research, covering subdomains such as maintenance and inspection, safety and security, autonomous driving and control, transport planning and management, revenue management, transport policy and passenger mobility.

Target audience: All rail stakeholders

How it brings us closer to achieving better rail for Europe: It brings us closer by providing an in-depth summary of the current research focus. A specific emphasis was devoted to reviewing Shift2Rail projects, basing on publicly available information. From the review findings the deliverable determines some promising research directions to provide further uptake of AI in railways.

More information on this topic: RAILS 


Final version of Shift2Rail’s My-TRAC mobile application

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Description: This deliverable details the development of My-TRAC technologies that aim to provide an improved passenger experience and personalised travel recommendations by utilising an ecosystem of models for user choice simulation, data, and behavioural analytics, and implement different components (i.e., the social market, the operators’ portal, and 3rd parties’ services).

Target audience: Final users (travellers and freight transport users); Operators (rail operator companies)

How it brings us closer to achieving better rail for Europe: It brings us closer by combining different technologies and datasets to be able to provide to its users personalised recommendations. Nowadays, passengers demand accurate and tailored information (points of interest, itineraries, level of crowdedness) to take informed decisions.

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Roadmap for My-TRAC mobile application improvements and extension

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Description: This deliverable presents the potential improvements for further development of the My-Trac application, based on the analysis of the onsite pilots and the virtual experiments. It suggests ameliorations to improve the user experience, the usability of the application, and the models integrated in the app.

Target audience: Final users (travellers and freight transport users); Operators (rail operator companies)

How it brings us closer to achieving better rail for Europe: It brings us closer by optimising My-TRAC technologies and extending the application, allowing travellers to have a useful tool of multimodality in their hands that can guide them from A to B and improve their travel experience.

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A First modelling framework of Conceptual Data Model (CDM) for use case developments

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Description: This deliverable contains the first modelling framework and the first model structure, including information layers available for Linx4Rail Work Package 4.

Target audience: All rail stakeholders

How it brings us closer to achieving better rail for Europe: It brings us closer by establishing the standard for interactions between legacy and new systems. ensuring sustainable interoperability. It provides the models’ federation, global system modelling specifications and a strategy for implementation of technological breakthroughs.

More information on this topic:  LINX4RAIL 1

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